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FEM-Simulated AI Training

Placeholder for a future study using FM-FEM to generate synthetic ultrasonic datasets for machine learning defect detection.

We plan to use our FM-FEM platform to generate large synthetic datasets under controlled geometry and defect conditions. These datasets will be used to train machine learning classifiers that can infer defect type, size, and location from noisy waveforms.

The approach offers explainable, uncertainty-aware models and reduces the reliance on physical test specimens during development.